应用场景打开，AI 助推金融机构内部效 率与外部价值双升 [Table_Industry] 计算机 "AI+金融"系列专题研究（二） [Table_Invest] 本报告导读： 当前，AI 应用已在各类金融机构的核心业务以及中后台场景中加速渗透，助推金融 机构内部效率与外部价值双升。 投资要点： 告 请务必阅读正文之后的免责条款部分 股 票 研 究 行 业 专 题 研 究 证 券 研 究 报 股票研究 /[Table_Date] 2025.11.24 [Table_Report] [table_Authors] 2025-11-25 [Table_Summary] 投资建议：2025 年 DeepSeek R1 的发布助推通用模型推理能力跃迁 和成本锐减，并实现模型开源，成为金融机构本地化部署 AI 的行业 拐点。当前，AI 应用已在各类金融机构的核心业务以及中后台场景 中加速渗透，未来 AI 有望重构金融业务流程和组织架构，为金融数 智化打开新纪元。建议关注：1）金融信息服务。相关标的：同花顺、 九方智投控股、指南针。2）第三方支付。推荐标的：新大陆、新国 都，相关标的：拉卡拉。3）银行 IT。推荐标的：宇 ...

意见领袖丨中国金融杂志 作者 | 王忠民'全国社保基金理事会原副理事长'AI金融时代的来临，意味着从技术深耕到生态重构的深 度探索，使金融服务实现精准化、普惠化、生态化升级 AI金融时代的来临，意味着从技术深耕到生态重构的深度探索，使金融服务实现精准化、普惠化、生 态化升级。金融融入"AI原生"的新型经济模型，让产业增长具备自我加速、自我进化的能力。对居民而 言，智能客服的语义理解能力则让人力得以专注于处理更复杂的需求。这一转型本质上是金融从规模经 济向范围经济的跃迁，数据要素的边际成本趋近于零，实现"长尾服务"。构建"技术突破—数据治理— 伦理合规"的协同框架，重塑消费与金融服务模式，共同创造全新商业需求。这也正是国务院2025年8月 发布的《关于深入实施"人工智能+"行动的意见》赋予金融业推动人工智能与金融业务的深度融合，形 成"技术赋能金融、金融服务实体"的任务所在。在国内刚需与国际竞争日趋加剧的趋势下，AI时代的中 国金融品牌保持世界领先水平应有强烈的紧迫性。 AI成为推动银行品牌高质量发展的重要引擎之一 《关于深入实施"人工智能+"行动的意见》明确提出，到2027年金融领域智能终端普及率超70%，2 ...

Group 1 - The core viewpoint of the news highlights the positive performance of the AI-focused ETF, with a 1.45% increase and a "V" shaped market trend, indicating strong upward momentum [1] - The ETF's constituent stocks showed robust performance, with 26 out of 30 stocks rising, led by Hehe Information with a 6.40% increase, and several others exceeding 4% [1] - The trading volume was significant, exceeding 54 million yuan with a turnover rate of 18.4%, indicating increased liquidity and potential for further capital allocation [1] Group 2 - The 2025 Yunqi Conference reinforced the narrative of growing demand in China's AI and cloud sectors, with continuous improvements in model capabilities, infrastructure, and application ecosystems [2] - The outlook for Alibaba Cloud remains positive, with expectations of accelerating revenue growth on a quarterly basis [2] - The AI-focused ETF closely tracks the STAR Market AI Index, covering high-quality enterprises across the entire industry chain, benefiting from high R&D investment and policy support [2]

Core Insights - The banking industry is rapidly adopting AI applications, with over 100 new scenarios announced by major banks like ICBC, CCB, and BOC as of June 2025, indicating a significant shift towards AI integration in financial services [1][5][6] - A report from Tencent Financial Research Institute highlights that by mid-2025, 79 AI-related projects were awarded in the financial sector, with banks accounting for over half of these projects [1][2] - The Chinese government aims for over 70% application penetration of new intelligent terminals and agents by 2027, increasing to over 90% by 2030, emphasizing the importance of AI in various sectors, including finance [1] AI Application Expansion - Major banks have reported substantial increases in AI application scenarios, with CCB announcing 274 scenarios, up from 193 in 2024, and CITIC Bank claiming over 1,600 scenarios [5][6] - The trend shows that more small and medium-sized banks are beginning to disclose their AI application details, indicating a broader industry engagement with AI technologies [6][8] Efficiency Improvements - AI applications have led to significant efficiency gains, with banks like China Merchants Bank reporting a reduction of 4.75 million hours in labor through AI, translating to approximately 390 million yuan in economic benefits [8] - Traffic Bank reported a 67% increase in output rates and an 83% increase in withdrawal rates through AI deployment in personal banking [8] Challenges in AI Implementation - Despite the rapid adoption, many financial institutions are still in the early stages of AI implementation, facing challenges in integrating AI into core business functions [3][10] - The effectiveness of AI applications varies significantly based on the chosen business scenarios, with some applications proving more successful than others [14][15] Organizational Changes - The integration of AI is prompting a restructuring of banking operations, with a shift from traditional roles to new positions focused on AI and data science [18][20] - Banks are increasingly emphasizing the need for collaboration between technology and business departments to effectively implement AI solutions [20][21] Regulatory Considerations - The financial sector is highly regulated, and the application of AI technologies raises concerns regarding compliance and risk management, necessitating careful oversight [22][23] - Financial institutions are advised to ensure that AI applications align with regulatory requirements and to maintain human oversight in critical decision-making processes [22][25]

Core Insights - The integration of "digital intelligence" and "finance" is creating innovative practices that enhance financial services and support high-quality development [1] - Financial services are increasingly utilizing AI technology, transforming from passive to proactive engagement with customers [1] - Cross-border payment solutions are being enhanced through technological innovations, addressing pain points for foreign visitors in China [2] Group 1: Financial Services Innovation - The financial service exhibition at the China International Fair for Trade in Services showcased the deep integration of AI in finance, with practical applications like intelligent robots providing customer service [1] - Banks are implementing personalized financial solutions through interactive technologies, such as retirement calculators and AR glasses for elderly clients [1] - Financial institutions are focusing on enhancing service breadth and depth by directing resources towards technological innovation [3] Group 2: Support for Technological Innovation - Financial institutions are actively supporting tech innovation by providing comprehensive services across various financial products, including equity investment plans and specialized insurance [3] - The China Banking sector is promoting significant financial support for AI and technology projects, with initiatives like a 1 trillion yuan AI support plan [3] - The financial sector is increasingly utilizing data analytics to provide precise support for small and medium enterprises, enhancing the efficiency of green finance [4] Group 3: Financial Growth Metrics - As of June, loans related to the "five major articles" in finance accounted for approximately 70% of the total loan increment, with growth rates surpassing overall loan growth [5] - The ongoing transformation in finance is reshaping its boundaries while simultaneously catalyzing technological breakthroughs [5]

Core Insights - The company has been awarded the "Best Private Bank in China" for the ninth time by The Asset, highlighting its excellence in comprehensive services within the private banking sector [1][9] Group 1: Business Philosophy and Strategy - The company adheres to the business philosophy of "Integrity and Stability," focusing on national needs, financial capabilities, client expectations, and its own strengths [4] - It has integrated group resources to form a service team of nearly 10,000 people, leading the development of private banking in China [4] Group 2: Wealth Management Services - The company emphasizes a client-centric approach, integrating various investment tools and services to meet diverse client needs [5] - It has generated over 1.2 million professional configuration reports to assist clients in liquidity management, capital preservation, and asset allocation [5] - The company is building an open product ecosystem that matches the diverse needs of clients [5] Group 3: Family and Business Services - The company has launched the "ICBC Chuan Cheng Family" service system, focusing on comprehensive family wealth management, including governance and charitable services [6] - It has established partnerships with over 100 organizations in areas such as trust, insurance, and education to enhance its family services [6] Group 4: Entrepreneurial Support - The company aims to be the "Entrepreneur Partner Bank," providing a comprehensive service ecosystem for entrepreneurs [7] - It has organized nearly 4,000 regional enterprise visits, benefiting over 60,000 entrepreneurs by creating platforms for exchange and collaboration [7] Group 5: Philanthropy and Social Responsibility - Under the "ICBC Bright Action" public welfare brand, the company has engaged in various charitable projects, benefiting nearly 50,000 students in Sichuan [8] - It is exploring new paradigms of "Finance + Charity" to help entrepreneurs fulfill their social responsibilities [8] Group 6: Recognition and Authority - The Asset magazine's 3A award is a prestigious recognition in the Asia-Pacific region for outstanding contributions in wealth management and private banking [9] - The repeated recognition of the company as "Best Private Bank in China" signifies its long-standing professional acknowledgment in the industry [9]

Core Viewpoint - The banking industry is actively pursuing AI development, with various banks announcing projects related to AI capabilities, indicating a significant trend towards AI integration in financial services [1][4][6]. Group 1: AI Deployment Strategies - Different types of banks are forming differentiated AI development paths based on regional characteristics, customer structures, and digitalization foundations [2][5]. - State-owned banks tend to be conservative in their application of financial vertical models, focusing on foundational applications, while city commercial banks and joint-stock banks show a stronger willingness for transformative AI strategies [5]. - Current implementations show that state-owned banks are building platforms and ecosystems, while joint-stock banks emphasize scalability and systematic construction [5]. Group 2: Commonalities Across Banks - All types of banks are focused on how AI can enhance customer experience, optimize business processes, reduce operational costs, and strengthen risk control [6]. - As of August, 31% of customer service centers and remote banking have completed large model deployments within banks [6]. - The total financial technology investment by the six major state-owned banks reached 125.46 billion yuan, a year-on-year increase of 2.15% [6]. Group 3: Challenges in AI Application - The application of AI in financial institutions is primarily focused on general areas, with lower penetration in critical business areas such as marketing and risk control [7][8]. - Three core challenges hinder deeper AI application: technology maturity, professional requirements, and cost considerations [8]. - Financial institutions are currently in a phase of observing and experimenting with AI, particularly in general scenarios, while being cautious in core business areas [8]. Group 4: Technology and Market Dynamics - The integration of finance and AI is driving a dual upward spiral of "technology" and "market" [10]. - Financial institutions are feeling anxious about how to effectively utilize advanced technologies like large models, especially as peers achieve breakthroughs [10]. - The current stage is primarily driven by technology, but as banks recognize AI's value, business demands will increasingly shape technology development [10][11].

Group 1: Transition from Digital Banking to AI Banking - The banking industry is transitioning from digital banking to AI banking, with 2024 being recognized as the "Year of Large Model Applications" [1][2] - AI technologies with deep reasoning and cross-modal capabilities are reshaping the operational environment of banks [2] - The foundational AI strategy for banks includes generative large models and reasoning models, catering to diverse application needs [3][4] Group 2: AI Applications in Banking - Banks are implementing AI applications across various scenarios, including intelligent coding, marketing, customer service, risk control, compliance, and daily management processes [5] - Notable examples include CITIC Bank's integration of AI decision-making and generative models, and China Merchants Bank's AI assistant achieving a 95% accuracy rate in customer intent recognition [5][8] - The number of AI application scenarios disclosed by banks has surged, with major banks like ICBC and CCB enabling numerous applications across various business areas [11] Group 3: Human-AI Collaboration - The relationship between humans and AI is increasingly emphasized, focusing on how employees can effectively utilize AI technologies [9] - Banks are investing significantly in financial technology, with a total investment of 125.46 billion yuan in 2024, reflecting a 2.15% increase from 2023 [11] - The workforce in technology roles is expanding, with notable increases in the number of tech personnel across major banks [12] Group 4: Opportunities and Challenges - AI's widespread application is a key driver of digital transformation in banking, enhancing operational efficiency and customer experience [16] - The banking sector faces challenges related to algorithm compliance, data privacy, and the need for robust AI governance [19][22] - The accuracy of leading financial models is around 95%, indicating ongoing challenges in AI reliability and the need for continuous improvement [22] Group 5: Future Outlook - The integration of AI in banking is expected to lead to comprehensive automation and intelligent services, fundamentally changing operational models [17][23] - The year 2025 is anticipated to be a pivotal period for rapid AI application growth in the financial services sector [23]

Core Insights - The rapid development of financial technology is driving banks to adopt large model technology as a core driver for transformation and innovation, with many banks actively engaging in this area by 2025 [2] Group 1: Industrial Leadership - Industrial and Commercial Bank of China (ICBC) leads in large model application, having launched the "ICBC Zhiyong" system, which has surpassed 1 billion calls by Q2 2025, enhancing over 20 core business areas and 200 application scenarios [3] - ICBC's application scenarios increased by 67% year-on-year compared to 2024, with call frequency rising by 120%, showcasing significant scaling effects [3] - The system has improved foreign exchange trading decision response speed by 80% and increased trading execution efficiency by 300%, with related business revenue up 15% year-on-year in the first half of 2025 [3] Group 2: Technological Deployment - Agricultural Bank of China has successfully deployed the DeepSeek model internally, enhancing business innovation and operational efficiency across various processes [5] - Huaxia Bank has implemented DeepSeek for various applications, improving office efficiency and customer service through intelligent Q&A and report generation tools [6] - Jiangsu Bank utilizes DeepSeek for intelligent contract quality inspection and automated valuation reconciliation, achieving over 90% success in identification [7] Group 3: Customer Service Enhancements - Customer service improvements include a 30% increase in marketing conversion rates through targeted marketing strategies based on customer data analysis [7] - Customer satisfaction has risen from 80% to over 90% due to enhanced intelligent customer service capabilities [7] - Beijing Bank has developed a proprietary "Jingzhi" large model, focusing on building an AI platform for various applications [8] Group 4: Future Directions - Shanghai Bank is constructing a "large model + micro model" collaborative system to enhance service delivery and operational efficiency across various financial services [9] - Chongqing Bank plans to leverage large models for broader applications in marketing, risk control, and internal management by 2025 [8] - The overall trend indicates that banks are not only improving their operational efficiency and service quality but also contributing valuable experiences for the digital transformation of the banking industry [10]

Core Insights - The integration of artificial intelligence (AI) into the financial industry is accelerating, driven by technological advancements, regulatory improvements, and market dynamics [1][2][3] - AI is not only enhancing efficiency but also transforming the underlying principles and operational paradigms of the financial sector, marking the beginning of a new journey rather than the end of financial innovation [1][3] Technological Advancements - The rise of generative AI and large models has redefined the capabilities and application scenarios of AI, with over 130 domestic large models launched in China in 2023, many with parameters reaching hundreds of billions [2][3] - Scene-specific large models, tailored to the financial industry's unique context and data structures, are becoming essential for AI's role in financial reform and innovation [3][14] Operational Efficiency - AI is deeply embedded in financial institutions' backend processes, enabling automation of routine tasks, which reduces human error and significantly lowers labor costs [6][7] - AI enhances customer service through personalized recommendations and intelligent customer support, allowing financial institutions to deliver tailored services [6][7] Risk Management - AI constructs a comprehensive security loop for risk management, improving the ability to identify potential fraud and money laundering risks in real-time [7][9] - Regulatory frameworks are evolving to ensure the safe and sustainable development of AI in finance, focusing on institutional design, pilot exploration, and technological oversight [9][10] Regulatory Environment - Recent government policies emphasize AI as a foundational support for digital finance, encouraging financial institutions to adopt new technologies for enhanced service capabilities [9][11] - Regulatory sandboxes are being implemented to provide a controlled environment for testing new AI applications, facilitating innovation while managing risks [10][11] Market Participation - Capital markets are increasingly investing in AI-driven financial technology companies, with over 90% of newly listed tech companies having received venture capital support [11][12] - The bond market has also seen significant growth, with a cumulative issuance of 1.2 trillion yuan in technology company bonds by the end of 2024, reflecting strong market confidence in AI technologies [12] Future Outlook - The fusion of AI and finance is evolving into a model-level revolution, with predictions indicating that generative AI could generate approximately 3 trillion yuan in commercial value for the financial sector [12][14] - The future of "AI + finance" will focus on scenario-driven development, human-machine collaboration, and ecosystem building, leading to a more systematic and sustainable growth phase [12][15]